Fractal biomarker of daily activity for women with early onset depression.

Abstract

Background: Depression is a major health issue in adolescence and young adulthood, emphasising the need for early risk identification. Patients with major depressive disorder (MDD) often show disturbed daily rest-activity patterns, but such changes are often confounded by medication intake, comorbidities and disease duration.

Objective: In this exploratory analysis, we tested whether there are specific changes in daily rest activity (from wrist-worn actigraphy) in women at the onset of MDD without medication, as compared with age-matched controls.

Methods: Participants from the MDD group (age 19-32, 24.73±5.13 (mean±SD), N=15) and control group (age 20-31, 24.89±3.82, N=9) completed ~7 day ambulatory actigraphy recordings, followed by a stringently controlled circadian laboratory protocol to assess endogenous circadian melatonin levels. We analysed the daily rhythm of mean activity levels and non-linear fractal dynamics in eight 3-hour time bin across the 24 hours, correlating these measures with depressive symptom severity and endogenous melatonin levels.

Findings: Using approaches from non-linear fractal dynamics, we showed that, compared with healthy controls, women at MDD onset had a higher fractal activity correlation (FAC) during the last hours of sleep, indicating more 'wake-like' patterns (FAC within 0-3 hour before wake: 0.92±0.64 (SD) in MDD vs 0.77±0.18 in controls, p=0.02). The alteration was independent of mean activity level and wake duration but appeared to be associated with depressive symptom severity (p=0.08). Moreover, there was a trend association for altered FAC with endogenous melatonin levels in the MDD group (for onefold increase in melatonin level in the last 3 hours before wake, the FAC increased by 0.33±0.17 (SE), p=0.08).

Conclusions: Pre-wake FAC is elevated in unmedicated women at MDD onset and may serve as a potential biomarker associated with symptom severity and circadian physiology.

Clinical implications: These findings provide proof-of-concept evidence that unique fractal motor activity patterns may support early detection of MDD.